We present a new scale-adaptive ICP (Iterative Closest Point) method which aligns two objects that differ by rigid transformations (translations and rotations) and uniform scaling. The motivation is that input data may come in different scales (measurement units) which may not be known a priori, or when two range scans of the same object are obtained by different scanners. Classical ICP and its many variants do not handle this scale difference problem adequately. Our novel solution outperforms three different methods that estimate scale prior to alignment and a fourth method that, similar to ours, jointly optimizes for scale during the alignment.
NETL
NSTL
Elsevier
